DocumentCode
1985601
Title
Adaptive neuro-fuzzy inference system for speckle noise reduction in SAR images
Author
Basturk, Alper ; Yuksel, M. Emin
Author_Institution
Dept. of Comput. Eng., Erciyes Univ., Kayseri
fYear
2007
fDate
12-15 Feb. 2007
Firstpage
1
Lastpage
4
Abstract
An adaptive neuro-fuzzy inference system (ANFIS) based method is proposed for speckle noise reduction in synthetic aperture radar (SAR) images. Before using active RADAR (radio detection and ranging) and SAR imageries, the very first step is to reduce the effect of speckle noise. Reduction of speckle noise is one of the most important processes to increase the quality of radar coherent images. Filtering is the common method which is used to reduce the speckle noise. For this purpose, two ANFISs are trained and outputs of these systems are converted to one output through a mean calculator in this work. Performance of the proposed method is compared with performances of state-of-the-art methods in the literature for speckle noise reduction. Results are presented by filtered images and a table.
Keywords
fuzzy neural nets; fuzzy reasoning; image denoising; radar imaging; speckle; synthetic aperture radar; ANFIS; SAR images; active RADAR image; adaptive neuro-fuzzy inference system; radar coherent images; speckle noise reduction; synthetic aperture radar images; Adaptive optics; Adaptive systems; Image converters; Noise reduction; Optical surface waves; Radar imaging; Radar remote sensing; Remote sensing; Speckle; Synthetic aperture radar;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on
Conference_Location
Sharjah
Print_ISBN
978-1-4244-0778-1
Electronic_ISBN
978-1-4244-1779-8
Type
conf
DOI
10.1109/ISSPA.2007.4555350
Filename
4555350
Link To Document